Accession Number : AD0736958
Title : Stochastic Approximation Type Algorithms for the Optimization of Constrained and Multinode Stochastic Problems.
Descriptive Note : Technical rept.,
Corporate Author : BROWN UNIV PROVIDENCE R I CENTER FOR DYNAMICAL SYSTEMS
Personal Author(s) : Kushner,Harold J.
Report Date : JAN 1972
Pagination or Media Count : 67
Abstract : The aim of the paper is the development of a structure for stochastic optimization algorithms (of the Monte-Carlo or stochastic approximation type) which is analogous to that used in non-linear programming. The developed structure is quite versatile, and seems to consider the elements of the problem in a very natural manner from both the theoretical and practical viewpoints. A second paper is also included in the report, titled: Stochastic Approximation Algorithms for the Local Optimization of Functions With Non-Unique Stationary Points.
Descriptors : (*NONLINEAR PROGRAMMING, OPTIMIZATION), APPROXIMATION(MATHEMATICS), ITERATIONS, RANDOM VARIABLES, THEOREMS, STOCHASTIC PROCESSES, ALGORITHMS
Subject Categories : Operations Research
Distribution Statement : APPROVED FOR PUBLIC RELEASE